Summary of Incident Longwave Conditions
Wave Direction (deg az., coming from)
Frequency increments are 0.0001 Hz for periods of 25-80 sec and 0.00006 Hz for periods of
One water level was tested. The tide range at Tutuila is relatively small, with
a mean range of 0.76 m (2.5 ft). Harbor wave response is unlikely to vary much
with water level over this tidal range. The water level was selected as mean low
water, the reference datum for bathymetric data.
Calculation of spectra
Numerical model test results for short waves in Pago Pago Harbor
embayment are all based on spectral postprocessing of the initial CGWAVE runs.
For the parameter settings used in short wave runs (Table 3), incident wave
height had no significant impact on amplification factors at study sites. Hence,
short-wave amplification factors are all computed in the form of (Aamp)eff as
described by Thompson et al. (1996). This approach requires, first, that
CGWAVE be run with the range of wave periods and directions to be considered
in the spectral calculations. Second, for each value of peak wave period, Tp , and
wave approach direction, θp; a spectral peak enhancement factor, γ; and
directional spreading factor, s, must be specified. The Tp and θp values were
taken to represent bins in the 5-year hindcast summaries. Values for γ and s were
approximated by the same procedure developed in the previous study. This
procedure has been further tested and become a standard approach in CHL
spectral wave model studies (Smith, Sherlock, and Resio 2001).
In order to obtain special coverage of areas where harbor operations would
most likely be affected by wave conditions, output lines were selected to cover
mooring areas along all proposed alternative harbor areas (Figure 13). The
saving sequence began with the south end of the line at the Anasosopo site and
proceeded counter clockwise into the embayment, as indicated in the figure.
Model results were saved at regular intervals along each line, with interval width
ranging from 15.1 m (50 ft) to 39.1 m (128 ft).
Chapter 3 Numerical Model